Quality of service is defined as the capability of the network to transport information across the network while satisfying some communication performance requirements of applications, such as low delay, low loss, or high throughput. Given the reality that the amount of traffic to be sent over a network may exceed its capacity, any QoS mechanism must also be capable of providing different levels of QoS to different types of traffic in accordance with externally specified policies related to priority (also referred to as Class of Service). Providing end-to-end (E2E) QoS assurances in a converged network is indeed a challenging task.
Converged networks mean a combination of diverse networks over which services are provided. Diversity is with respect to the organizations that control the networks. In addition, it is assumed that an organization has no control over networks that do not belong to it. Thus, the challenge for an organization lies in providing QoS for flows that traverse networks that are not under the control of that organization. Such networks which are not under the control of that organization are called opaque networks. This also implies that the organization cannot expect to know directly of the state of the opaque network or networks but instead will have to infer their state, and using this inference, the organization will have to depend on mechanisms to ensure QoS for the flows. Such converged networks are expected to transport a wide spectrum of applications each with very diverse QoS requirements. These challenges have inspired a number of approaches in the prior art.
One such approach describes using “time-delay” measurements to describe the characteristics of opaque networks. In addition the approach is based on active probes. (S. Valaee & B. Li, “Distributed call admission control for ad hoc networks”, published in the proceedings of the VTC'02). While this is a good approach for certain types of networks, it suffers from the following severe drawbacks: (a) It is expensive in terms of the “overheads” introduced in order to derive latency estimates, (b) it is limited to wireline networks, and (c) it does not consider multiple service (traffic) classes. Hence such an approach, albeit good for the environments that it has been proposed for, cannot be used (nor extended without having to undergo major transformations) to solve the problems associated with such converged networks.
Others considered measurement based admission control (MBAC). MBAC schemes use measurements to characterize the current load. Such algorithms have been shown to achieve much higher utilization than parameter-based admission control algorithms (S. Jamin, P. Danzig, S. Shenker and L. Zhang, “A measurement based admission control algorithm for integrated services packet networks”, IEEE/ACM Trans. on Networking, 5, Feb. 1997. 56-70). L. Breslau and S. Jamin and S. Shenker in “Comments on the performance of measurement-based admission control algorithms”, Infocom 2000, have shown that different MBAC algorithms all achieve almost identical levels of performance. These MBAC algorithms still however suffer from the requirement of complete knowledge and control over the elements in the path of the data packets.
It is therefore an object of the invention to provide methods and systems for use in network management systems for converged wireless networks that can better provide/sustain QoS assurances to the wide spectrum of applications that use such converged networks that overcome the deficiencies in the prior art.